Improved cortical thickness measurement from MR images using partial volume estimation

Accurate cortical thickness estimation is important for the study of many neurodegenerative diseases. Amongst the approaches previously proposed in the literature, mesh based techniques typically lack computational efficiency, whereas voxel based techniques tend to be faster but are less accurate. The aim of this work is to propose a novel voxel based method using the Laplacian definition of thickness, being both accurate and computationally efficient. A subvoxel estimate of the location of the boundary is obtained through ray-casting using both partial volume estimation and the direction of the streamlines. This estimate is then used to initialise the boundary conditions when computing the length of the streamlines. The approach was validated on synthetic phantoms and real data, showing an improved accuracy and reproducibility.